Simultaneous sensor placement and pressure reducing valve localization for pressure control of water distribution systems

Many studies on pressure sensor (PS) placement and pressure reducing valve (PRV) localization in water distribution systems (WDSs) have been made with the objective of improving water leakage detection and pressure reduction, respectively. However, due to varying operation conditions, it is expected to realize pressure control using a number of PSs and PRVs to keep minimum operating pressure in real-time. This study aims to investigate the PS placement and PRV localization for the purpose of pressure control system design for WDSs. For such a control system, a PS should be positioned to represent the pressure patterns of a region of the WDS. Correspondingly, a PRV should be located to achieve a maximum pressure reduction between two neighboring regions. According to these considerations, an approach based on the k-means++ method for simultaneously determining the numbers and positions of both PSs and PRVs is proposed. Results from three case studies are presented to demonstrate the effectiveness of the suggested approach. It is shown that the sensors positioned have a high accuracy of pressure representation and the valves localized lead to a significant pressure reduction

Battle of the Attack Detection Algorithms:Disclosing cyber attacks on water distribution networks

The BATtle of the Attack Detection ALgorithms (BATADAL) is the most recent competition on planning and management of water networks undertaken within the Water Distribution Systems Analysis Symposium. The goal of the battle was to compare the performance of algorithms for the detection of cyber-physical attacks, whose frequency increased in the past few years along with the adoption of smart water technologies. The design challenge was set for C-Town network, a real-world, medium-sized water distribution system operated through Programmable Logic Controllers and a Supervisory Control And Data Acquisition (SCADA) system. Participants were provided with datasets containing (simulated) SCADA observations, and challenged with the design of an attack detection algorithm. The effectiveness of all submitted algorithms was evaluated in terms of time-to-detection and classification accuracy. Seven teams participated in the battle and proposed a variety of successful approaches leveraging data analysis, model-based detection mechanisms, and rule checking. Results were presented at the Water Distribution Systems Analysis Symposium (World Environmental & Water Resources Congress), in Sacramento, on May 21-25, 2017. This paper summarizes the BATADAL problem, proposed algorithms, results, and future research directions

Optimization Methodology for Estimating Pump Curves Using SCADA Data

Water distribution systems (WDSs) deliver water from sources to consumers. These systems are made of hydraulic elements such as reservoirs, tanks, pipes, valves, and pumps. A pump is characterized by curves which define the relationship of the pump’s head gain and efficiency with its flow. For a new pump, the curves are provided by the manufacturer. However, due to its operating history, the performance of a pump deteriorates, and its curves decline at an estimated rate of about 1% per year. Pump curves are key elements for planning and management of WDSs and for monitoring system efficiency, to determine when a pump should be rehabilitated or replaced. In practice, determining pump curves is done by field tests, which are conducted every few years. This leaves the pump’s performance unmonitored for long time periods. Moreover, these tests often cover only a small range of the curves. This study demonstrates that in the era of IoT and big data, the data collected by Supervisory Control And Data Acquisition (SCADA) systems can be used to continuously monitor pumps’ performance and derive updated pump characteristic curves. We present and demonstrate a practical methodology to estimate fixed and variable speed pump curves in pumping stations. The proposed method can estimate individual pump curves even when the measurements are given only for the pumping station as a whole (i.e., total flow, pumping station head gain). The methodology is demonstrated in a real-world case study of a pumping station in southern Israel

Reliability of a Contamination-Detection Sensor Network in Water Distribution Systems during a Cyber-Physical Attack

The vastness of water distribution systems (WDS) makes them vulnerable to exposure to different types of accidental/intentional contamination. Although most such contamination events that occurred in the recent past were accidental, criminal intent was involved in a few. Considering the accessibility of WDS and the potentially harmful outcomes of drinking-water contamination, online water-quality monitoring sensors are typically positioned in selected locations throughout WDS as a preventive strategy. These sensors, once positioned, communicate over a cyber-infrastructure layer and are liable to cyber-physical attacks—the sensor and/or its communication system becoming compromised or the sensor network becoming malfunctioned such that part of its components is deactivated. However, the sensor network placement state-of-the-art has thus far overlooked these cyber-physical attack scenarios. The current study attempts to overcome this limitation in the state-of-the-art by developing and demonstrating a methodology for evaluating the impact of a cyber-physical attack on a sensor network, compromising its functionality partially. Our proof-of-concept, using a simple network and a straightforward cyber-physical attack scenario, has revealed the vast potential of examining the performance of sensor networks under accidental/intentional malfunctioning and providing valuable information for decision makers in water utilities and regulators

Resilience Assessment of Water Quality Sensor Designs under Cyber-Physical Attacks

Water distribution networks (WDNs) are critical infrastructure for the welfare of society. Due to their spatial extent and difficulties in deployment of security measures, they are vulnerable to threat scenarios that include the rising concern of cyber-physical attacks. To protect WDNs against different kinds of water contamination, it is customary to deploy water quality (WQ) monitoring sensors. Cyber-attacks on the monitoring system that employs WQ sensors combined with deliberate contamination events via backflow attacks can lead to severe disruptions to water delivery or even potentially fatal consequences for consumers. As such, the water sector is in immediate need of tools and methodologies that can support cyber-physical quality attack simulation and vulnerability assessment of the WQ monitoring system under such attacks. In this study we demonstrate a novel methodology to assess the resilience of placement schemes generated with the Threat Ensemble Vulnerability Assessment and Sensor Placement Optimization Tool (TEVA-SPOT) and evaluated under cyber-physical attacks simulated using the stress-testing platform RISKNOUGHT, using multidimensional metrics and resilience profile graphs. The results of this study show that some sensor designs are inherently more resilient than others, and this trait can be exploited in risk management practices

Water-energy nexus in a desalination-based water sector: the impact of electricity load shedding programs

Abstract Reliance on water production by desalination as a solution to water scarcity is growing worldwide. High energy demands of seawater desalination raise new challenges for both water and energy management and highlight the importance of understanding the operational dependencies of the water sector on energy supplies. This study provides an in-depth analysis of the impact of the water-energy nexus in a desalination-based water sector, using Israel as a case study. Being large energy consumers, desalination plants are part of the Electricity Load Shedding Program (ELSP), which government energy regulators invoke in times of energy shortage. We focus on the interdependency between the two sectors as manifested at the time of ELSP utilization during an extreme heat wave. We show that energy shedding compensation is 6 to 14 times greater than the economic loss to the desalination plant from no water production, creating an obvious economic incentive to participate in ELSPs. However, this imbalance has a substantial negative impact on the water sector, which may compromise the level of service. Our evaluation concludes that the government authorities regulating water and energy need an official mechanism and policy for joint management strategies that can ensure economic efficiency and reduce the risk of power and water shortages during extreme events